Question

我有一个多年的每日栅格时间序列堆栈（ras_in），我需要按年计算累积总和(e.g. day1 = day1; day2 = day1 + day2; day3 = day1 + day2 + day3,...)

我正在尝试使用'cumsum'函数和Zapply，如下所示：

fun_my <- function(x){cumsum(x)}
out <- Zapply(ras_in, by=year, fun=fun_my, na.rm=T)

但是我收到以下错误：

FUN中的错误（newX [，i]，...）：未使用的参数（na.rm = TRUE）

我尝试：

fun_my <- function(x,na.rm=T){cumsum(x)}

但我收到另一个错误：

v [start：end，]：下标超出范围
时出错

有什么建议吗？万分感谢

Answer 1

可重复数据（2013-01-01至2015-12-31的栅格堆栈）：

library(raster)

r <- raster()

s <- stack(lapply(1:1095, function(x) setValues(x = r, values = sample(x = c(NA,1),size = ncell(r), replace = T))))

s <- setZ(s, seq(as.Date('2013-01-01'),as.Date('2015-12-31'), 'day'), 'days')

按年份子集并按年计算累积总和：

year <- c('2013', '2014', '2015')

r_list <- list()

for (i in 1:3) {
  r_list[[i]] <- calc(x = subset(s, which(format(getZ(s), "%Y") %in% year[i])), fun = cumsum)
}

结果是这样的（三个光栅堆栈，每天累计和，每年一个）：

## [[1]]
## class       : RasterBrick 
## dimensions  : 180, 360, 64800, 365  (nrow, ncol, ncell, nlayers)
## resolution  : 1, 1  (x, y)
## extent      : -180, 180, -90, 90  (xmin, xmax, ymin, ymax)
## coord. ref. : +proj=longlat +datum=WGS84 +ellps=WGS84 +towgs84=0,0,0 
## data source : in memory
## names       : layer.1, layer.2, layer.3, layer.4, layer.5, layer.6, layer.7, layer.8, layer.9, layer.10, layer.11, ## layer.12, layer.13, layer.14, layer.15, ... 
## min values  :       1,       2,       3,       4,       5,       6,       7,       8,       9,       10,       ## 11,       12,       13,       14,       15, ... 
## max values  :       1,       2,       3,       4,       5,       6,       7,       8,       9,       10,       ## 11,       12,       13,       14,       15, ... 
## 
## 
## [[2]]
## class       : RasterBrick 
## dimensions  : 180, 360, 64800, 365  (nrow, ncol, ncell, nlayers)
## resolution  : 1, 1  (x, y)
## extent      : -180, 180, -90, 90  (xmin, xmax, ymin, ymax)
## coord. ref. : +proj=longlat +datum=WGS84 +ellps=WGS84 +towgs84=0,0,0 
## data source : in memory
## names       : layer.366, layer.367, layer.368, layer.369, layer.370, layer.371, layer.372, layer.373, layer.374, ## layer.375, layer.376, layer.377, layer.378, layer.379, layer.380, ... 
## min values  :         1,         2,         3,         4,         5,         6,         7,         8,         ## 9,        10,        11,        12,        13,        14,        15, ... 
## max values  :         1,         2,         3,         4,         5,         6,         7,         8,         ## 9,        10,        11,        12,        13,        14,        15, ... 
## 
## 
## [[3]]
## class       : RasterBrick 
## dimensions  : 180, 360, 64800, 365  (nrow, ncol, ncell, nlayers)
## resolution  : 1, 1  (x, y)
## extent      : -180, 180, -90, 90  (xmin, xmax, ymin, ymax)
## coord. ref. : +proj=longlat +datum=WGS84 +ellps=WGS84 +towgs84=0,0,0 
## data source : in memory
## names       : layer.731, layer.732, layer.733, layer.734, layer.735, layer.736, layer.737, layer.738, layer.739, ## layer.740, layer.741, layer.742, layer.743, layer.744, layer.745, ... 
## min values  :         1,         2,         3,         4,         5,         6,         7,         8,         ## 9,        10,        11,        12,        13,        14,        15, ... 
## max values  :         1,         2,         3,         4,         5,         6,         7,         8,         ## 9,        10,        11,        12,        13,        14,        15, ...

与Zapply在R中的栅格累积总和

1 个答案: